ABSTRACT

The concept of neural network is originated from neuroscience. The networks formed by biological neurons, which are connected to carry out the functionalities typical of the nervous system in biological life forms, are referred as biological neural networks. The vast neural network has an elaborate structure with very complex interconnections. If the weights of a network were fixed from the beginning, neural networks could be implemented using any programming language in conventional computers. In the analog implementation of neural networks, a coding method is used in which signals are represented by currents or voltages. Analog and digital techniques for the hardware implementation of Artificial Neural Networks could be combined to provide a hybrid solution. Analog communication links could be used internally within an individual neural chip. Activation Functions have a wide range of applications in Sigma-pi and Hopfield neural networks in addition to being employed in multilayer perceptron neural network, chaotic and inertial neural networks.